A series of analytical and experimental work has been done to understand and describe the nature of the dynamics and pilot's recovery techniques in rotorcraft's power failure. Johnson (Ref. 1) analytically described the dynamics of rotorcraft's autorotation. Lee (Refs. 2, 3), Zhao (Refs. 4-6), Carlson (Refs. 7-10), and Okuno (Refs 11, 12) investigated the application of constrained optimization to investigate the safe operational envelopes for autorotation and reduced-power situations for a variety of rotorcraft ranging from single-engine (OH-58A, Refs. 2-3) to multi-engine, for instance UH-60A and Bell M430, (Refs. 4-6, 8, 11, 12, 10) to tilt-rotor (Refs. 7, 9, 10). Johnson (Ref. 1) investigated the autorotation of a helicopter from a hover, and Lee (Refs. 2, 3) refined the problem formulation by adding inequality constraints for thrust and vertical velocity. Lee postulated that the “avoid” regions in the height-velocity (H-V) restriction curve could be substantially reduced if optimal pilot inputs were used during autorotation. References 2 and 3 used a point-mass model of an OH-58A helicopter and the cost function was a weighted sum of the squared horizontal and vertical components of the helicopter velocity at touchdown. The point-mass model had two degrees-of-freedom (vertical and horizontal velocity) with an additional rotor speed degree-of-freedom. The inputs (horizontal and vertical thrust) required to minimize the cost function were computed using nonlinear optimal control theory. The correlation between flight data and the optimal results established the adequacy of the use of a point mass model in the optimal helicopter landing study (Ref. 2, 3). References 2 and 3 also validated the method by comparing the optimal profiles (helicopter states and controls) with available autorotation flight-test data for the OH-58A. A unique feature of the Refs. 2 and 3 formulation was the addition of path inequality constraints on components of both the control and the state vectors. The control variable inequality constraint is a reflection of the limited amount of thrust that is available to the pilot in the autorotation maneuver without stalling the rotor. The state variable inequality constraint is an upper bound on either the vertical sink rate of the helicopter or the rotor angular speed during descent. “Slack” variables were employed to convert these path inequality constraints into path equality constraints. The resultant two-point boundary-value problem with path equality constraints was successfully solved using the Sequential Gradient Restoration Algorithm (SGRA). With bounds on the control and state vectors, the optimal solutions obtained will realistically reflect the limitations of the helicopter and its pilot. The model in Ref. 2 and 3 used assumed zero-wind, vertical plane motion, and zero-slip flight. Zhao (Ref 4-6) extended the work by Lee (Ref. 2, 3) to investigate the takeoff and landing trajectories of a dual-engine helicopter in the event of a single engine failure. Zhao also used the SGRA for computing the optimal trajectories and used different constructions for the objective (cost) function to investigate optimal profiles for continued and rejected landings and takeoffs in the event of a single engine failure. In addition to touchdown velocity, horizontal distance was also included in the objective function to examine the implications of an engine failure on the safe return and landing or continued flight of the helicopter. A point-mass model of a UH-60A helicopter was used in this work with improvements to the model to include engine torque and a ground-effect model. Carlson (Ref. 7-10) launched from the previous body of work and used optimal control theory to investigate the unsafe (avoid) regions of the H-V envelope in the event of single-engine failure as well as complete engine failure situations in a civil tiltrotor aircraft and a dual engine helicopter. A relatively sophisticated three degree-of-freedom (vertical and horizontal velocity and pitch attitude) rotorcraft model was used with an added rotor speed degree-of-freedom and a non-linear aerodynamic model of the XV-15 tilt-rotor aircraft and the Bell M430 helicopter. An important contribution of the Refs. 7-10 work was the improvement in the optimization method. The Ref. 7-10 work demonstrated that the SGRA optimization method was not robust in the face of more complex problem formulations. The Refs. 7-10 work successfully implemented a direct method of optimization (Ref. 13) where the continuous two-point boundary value problem is discretized into a parameter optimization problem. The optimization used a well-established and mature nonlinear programming algorithm that is commercially available (Refs. 14, 15). The present invention applies a similar strategy to compute the optimal control inputs and resulting flight path for rotorcraft autorotation.